Toward efficient agnostic learning (1992)

by Michael J. Kearns , Robert E. Schapire , Linda M. Sellie , Lisa Hellerstein
Venue:In Proceedings of the Fifth Annual ACM Workshop on Computational Learning Theory
Citations:195 - 7 self

Active Bibliography

4 Part 1: Overview of the Probably Approximately Correct (PAC) Learning Framework – David Haussler - 1995
18 Probabilistic Analysis of Learning in Artificial Neural Networks: The PAC Model and its Variants – Martin Anthony - 1997
197 Efficient Distribution-free Learning of Probabilistic Concepts – Michael J. Kearns, Robert E. Schapire - 1993
6 Efficient Learning from Faulty Data – Scott Evan Decatur - 1995
40 Probably Approximately Correct Learning – David Haussler - 1990
Computational Learning Theory – Sally A. Goldman
12 Learning by Canonical Smooth Estimation, Part I: Simultaneous Estimation – Kevin L. Buescher, P. R. Kumar - 1996
2 Faithful Representations and Moments of Satisfaction: Probabilistic Methods in Learning and Logic – Lidror Troyansky, Prof Naftali Tishby - 1998
5 Agnostic Learning and Single Hidden Layer Neural Networks – Wee Sun Lee - 1996
!()+, -./01 23456 – Department Of Computer, David P. Dobkin, Dimitrios Gunopulos, Wolfgang Maass, Technische Universitaet Graz - 1995
5 On the Learnability of Discrete Distributions (Extended Abstract) – Michael Kearns, Yishay Mansour, Dana Ron, Ronitt Rubinfeld, Robert E. Schapire, Linda Sellie - 1994
We Will Give a Reduction Showing How Algorithm – Can Be - 1991
3 Knowledge acquisition in statistical learning theory – Shai Fine - 1999
288 Efficient noise-tolerant learning from statistical queries – Michael Kearns - 1998
93 On the learnability of discrete distributions – Michael Kearns, Ronitt Rubinfeld - 1994
18 Data Filtering and Distribution Modeling Algorithms for Machine Learning – Yoav Freund, Manfred K. Warmuth, David Haussler, David P. Helmbold - 1993
1 P-sufficient statistics for PAC learning k-term-DNF formulas through enumeration. – B. Apolloni, C. Gentile
Lower Bounds in . . . Learning Theory via Analytic Methods – Alexander Alexandrovich Sherstov - 2009
5 Learning with Limited Visibility – Eli Dichterman - 1998